What this category of data looks like
This category of data primarily comes from CRM systems, contract order databases, identity management systems, and product backends. Daily associated documents include customer onboarding application forms, tenant configuration sheets, administrator account lists, and delivery confirmation forms. Data fields include tenant unique identifiers, administrator account information, basic permission configuration items, onboarding application time, and delivery status. Data is updated per order or daily, synchronized with customer onboarding process progression or daily permission verification.
What constraints these characteristics impose on the tool calling and plugins workflow
Data sources for this category are scattered, and fields vary across systems. The tool calling and plugins workflow must implement automatic data pulling and field mapping across multiple systems to avoid format errors caused by manual entry. The uniqueness requirement for tenant configurations mandates that tool calls strictly isolate configuration parameters for different tenants to prevent cross-tenant data confusion. The data verification link must cover required fields such as tenant ID and administrator account to ensure parameter completeness before tool execution. Additionally, the delivery confirmation process relies on result feedback from tool calls, so tool execution status must be traceable to enable timely synchronization of delivery progress.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
toolChoice | "auto" or "none" | Select the corresponding mode based on whether the tenant initialization process requires active tool call triggering, in compliance with FastGPT v4.17.0 tool calling specifications |
functionCall | [{"name":"pullTenantConfig","parameters":{"tenantId":"{{tenant_id}}","adminAccount":"{{admin_account}}"}}] | Specify the tool function to call, pass core business parameters such as tenant ID and administrator account |
| Tool call timeout period | 30–60 seconds | Adapt to the average time required for pulling data across multiple systems, avoid process interruption due to excessive waiting time |
| Tool call retry count | 2–3 times | Address network fluctuations or temporary interface errors during single calls, improve process stability |
| Tool call result caching strategy | Retained for a single execution cycle | Avoid repeatedly pulling configuration data for the same tenant, improve initialization efficiency |
Three common mistakes
- Phenomenon: Tool call return results include redundant AI-native reply content, and trigger next-level branch execution at the same time. Cause: Output filtering rules for tool calls are not configured correctly, causing the workflow to retain both AI replies and tool execution results.
- Phenomenon: Qwen2.5 tool function calls do not respond during tenant initialization processes. Cause: The function call function is not correctly enabled in the model channel configuration, or required environment variables for AI Proxy are not fully configured.
- Phenomenon: Database plugin execution returns garbled Chinese data. Cause: The database connection plugin does not have the correct character set parameters configured, or character set verification rules are not added to the database permission configuration during tenant initialization.
How to confirm configurations are correct
- Run a single tenant initialization simulation process, check that the input parameters for tool calls include correct tenant ID and administrator account information.
- View AI Proxy service logs, confirm there are no missing environment variable errors, and that configuration data for the target tenant has been successfully pulled.
- Trigger the tool call retry logic, verify that the workflow can automatically resume execution when temporary interface errors occur.
- Run a database plugin connection test, confirm that Chinese data can be displayed normally with no garbled characters.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.